AI Engineer

Job Summary

We are seeking a motivated AI Engineer who, working under general direction, designs, builds, and operates AI-enabled capabilities in production environments. Responsible for implementing reliable AI services, products, and workflows, integrating with enterprise systems, and applying practical engineering discipline to deliver secure, maintainable solutions under real constraints.

Essential Duties

• Product Management
  • Designs and implements AI-enabled services, products, and workflows, taking use cases from POC and prototype through production release and maintenance.
  • Develops and maintains software components required to integrate AI capabilities into applications and operational workflows.
  • Establishes reliable delivery practices for AI services, including automated build/release patterns and operational readiness.
  • Maintains system behavior and performance, troubleshooting issues and driving improvements to reliability, latency, and cost.
  • Applies practical MLOps practices appropriate to the solution (versioning, evaluation, monitoring signals, and safe rollout patterns).
  • Reviews and improves code quality (including AI-assisted code) to ensure correctness, security, and maintainability.
  • Pairs with product and cross-functional stakeholders to translate requirements into deliverable scope, surfacing tradeoffs early and keeping work unblocked.
  • Documents system behavior, operational procedures, and key design decisions to support long-term supportability.
• Responsible & Compliant AI
  • Follows medical device quality system processes, documentation standards, and audit expectations.
  • Supports AI risk assessment, validation, traceability, and performance monitoring activities.
  • Contributes to explainability, bias evaluation, and safety controls.
  • Documents best practices and key learnings to support organizational knowledge sharing.
• Collaboration & Learning
  • Partners and collaborates with business stakeholders, Digital Transformation team, ITS team members, and Terumo Corporate associates to deliver enterprise and corporate solutions.
  • Documents methods, architecture decisions, and model evaluations.
  • Engages in continuous learning on medical device regulations, AI governance, and emerging AI technologies.
  • Mentors other team members and contributes to a collaborative, growth-oriented team culture.

Other Duties and Responsibilities

• Participates in evaluation of tools and approaches that improve engineering productivity and operational reliability of AI systems.
• Contributes to shared engineering standards and best practices across AI projects.
• Supports knowledge sharing through documentation, demos, education events, and peer collaboration.

Minimum Qualification Requirements

• Education: Bachelor’s degree in Computer Science, Software Engineering, Data Science, or related field; or equivalent education and experience sufficient to successfully perform the essential functions of the job may be considered.
• Experience: Minimum of 3 years of demonstrated experience building and operating production-grade software services, including exposure to AI/ML or LLM-based capabilities.
• Experience: Hands-on experience deploying and supporting solutions in production environments (Azure preferred) that integrate with enterprise systems and data sources.
• Experience: Experience with modern engineering practices, including source control, automated testing, and release management.
• Skills: Strong debugging and systems-thinking skills; ability to diagnose issues across service boundaries.
• Skills: Practical ability to deploy and operate AI/ML or LLM-based systems in real environments.
• Skills: Familiarity with MLOps or production support practices, such as versioning, evaluation signals, monitoring, and safe rollout patterns.
• Skills: Ability to make disciplined tradeoffs across scope, timelines, and operational risk.
• Skills: Clear written and verbal communication skills; effective collaboration across technical and non-technical teams.

Preferred Qualifications

• Exposure to: Medical device or healthcare industry (internship, course, lab, project)
• Experience with data platforms (Spark, Databricks, Hadoop)
• Experience with agent-based architecture or conversational AI platforms
• Understanding of regulated software concepts (e.g., GxP, ISO 13485, ISO 42001, MDSAP, IEC 62304*, SaMD guidance*)
• Familiarity with responsible AI, model interpretability, or bias mitigation
• Strong analytical and structured problem-solving skills.